|Dr. Fan Zhang||Georgia Institute of Technology||Distinguished Early Career Program||Distinguished Early Career Program Awards||$625,000|
A robot-assisted online monitoring, online maintenance, and dynamic risk assessment platform for LWRs and advanced reactors will be developed. This project will integrate a 3D nuclear power plant (NPP) digital twin with data from a pressurized water reactor (PWR) simulator to enable robotic navigation and manipulation research, and will be used to develop algorithms for autonomous fault detection, diagnosis, and risk assessment integrating robot assistance. Research will be demonstrated both virtually and in a real laboratory environment.
|Dr. Fan Zhang|
|Dr. Matteo Bucci||Massachusetts Institute of Technology||Distinguished Early Career Program||Distinguished Early Career Program Awards||$625,000|
This project will study boiling heat transfer and the boiling crisis in prototypical light water reactor (LWR) conditions. High-resolution optical diagnostics will be utilized to measure the time-dependent temperature, heat flux, and vapor phase distribution on the boiling surface, the vapor distribution and velocity in the flow. These measurements will allow finding an answer to long-standing dilemma related to the boiling of water and the boiling crisis in nuclear reactor conditions.
|Dr. Matteo Bucci|
|Dr. Amrita Basak||Pennsylvania State University||Distinguished Early Career Program||Distinguished Early Career Program Awards||$625,000|
The goal of this research is directed toward developing scientific and formalized physics-informed data-driven techniques toward accelerating the generation of both forward and inverse scaling laws that can be transferred across material systems or manufacturing processes to understand the fundamental linkages between processing and the properties of interest in metal additive manufacturing (AM).
|Dr. Amrita Basak|
|Dr. Brendan Kochunas||University of Michigan||Distinguished Early Career Program||Distinguished Early Career Program Awards||$625,000|
The objective of this project is to develop the fundamental methods and techniques that would leverage advanced modeling and simulation to create efficient and accurate hybrid or integrated (e.g. physics based + data driven + machine learning) models. The project will have 5 majors tasks: developing hybrid models, investigating efficient learning strategies, V&V, incorporating UQ, and developing a new flexible curriculum to teach these methods.
|Dr. Brendan Kochunas|
|Dr. Minghui Chen||University of New Mexico||Distinguished Early Career Program||Distinguished Early Career Program Awards||$625,000|
The objective of this integrated research and educational program is to perform separate effects tests (SETs) and integral effects tests (IETs) using a versatile molten salt test facility to validate system codes in support of the deployment of molten salt reactor (MSR) and Fluoride salt-cooled, High-temperature Reactors (FHRs) technologies and the expanded use of nuclear energy worldwide, and to offer students from undergraduate to graduate, especially Native American, Hispanic and underrepresented minorities, various training and education opportunities of advanced reactors and hands-on molten salt experiments.
|Dr. Minghui Chen|